SEARCH · Engineering Papers

Results for “sequencer”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

NASA NTRS1974

The subsequence weight distribution of summed maximum length digital sequences

An attempt is made to develop mathematical formulas to provide the basis for the design of pseudorandom signals intended for applications requiring accurate knowledge of the statistics of the signals. The analysis approach involves calculating the first five central moments of the weight distribution of subsequences of hybrid-sum sequences. The hybrid-sum sequence is formed from the modulo-two sum of k maximum length sequences and is an extension of the sum sequences formed from two maximum length sequences that Gilson (1966) evaluated. The weight distribution of the subsequences serves as an approximation to the filtering process. The basic reason for the analysis of hybrid-sum sequences is to establish a large group of sequences with good statistical properties. It is shown that this can be accomplished much more efficiently using the hybrid-sum approach rather than forming the group strictly from maximum length sequences.

Weathers, G. D.↗

NASA NTRS1983

Sequence of the 16S ribosomal RNA from Halobacterium volcanii, an archaebacterium

The sequence of the 16S ribosomal RNA (rRNA) from the archaebacterium Halobacterium volcanii has been determined by DNA sequencing methods. The archaebacterial rRNA is similar to its eubacterial counterpart in secondary structure. Although it is closer in sequence to the eubacterial 16S rRNA than to the eukaryotic 16S-like rRNA, the H. volcanii sequence also shows certain points of specific similarity to its eukaryotic counterpart. Since the H. volcanii sequence is closer to both the eubacterial and the eukaryotic sequences than these two are to one another, it follows that the archaebacterial sequence resembles their common ancestral sequence more closely than does either of the other two versions.

Gupta, R.↗

NASA NTRS1991

Archaebacterial rhodopsin sequences: Implications for evolution

It was proposed over 10 years ago that the archaebacteria represent a separate kingdom which diverged very early from the eubacteria and eukaryotes. It follows that investigations of archaebacterial characteristics might reveal features of early evolution. So far, two genes, one for bacteriorhodopsin and another for halorhodopsin, both from Halobacterium halobium, have been sequenced. We cloned and sequenced the gene coding for the polypeptide of another one of these rhodopsins, a halorhodopsin in Natronobacterium pharaonis. Peptide sequencing of cyanogen bromide fragments, and immuno-reactions of the protein and synthetic peptides derived from the C-terminal gene sequence, confirmed that the open reading frame was the structural gene for the pharaonis halorhodopsin polypeptide. The flanking DNA sequences of this gene, as well as those of other bacterial rhodopsins, were compared to previously proposed archaebacterial consensus sequences. In pairwise comparisons of the open reading frame with DNA sequences for bacterio-opsin and halo-opsin from Halobacterium halobium, silent divergences were calculated. These indicate very considerable evolutionary distance between each pair of genes, even in the dame organism. In spite of this, three protein sequences show extensive similarities, indicating strong selective pressures.

Lanyi, J. K.↗

NASA NTRS1999

Sequence information signal processor

An electronic circuit is used to compare two sequences, such as genetic sequences, to determine which alignment of the sequences produces the greatest similarity. The circuit includes a linear array of series-connected processors, each of which stores a single element from one of the sequences and compares that element with each successive element in the other sequence. For each comparison, the processor generates a scoring parameter that indicates which segment ending at those two elements produces the greatest degree of similarity between the sequences. The processor uses the scoring parameter to generate a similar scoring parameter for a comparison between the stored element and the next successive element from the other sequence. The processor also delivers the scoring parameter to the next processor in the array for use in generating a similar scoring parameter for another pair of elements. The electronic circuit determines which processor and alignment of the sequences produce the scoring parameter with the highest value.

Peterson, John C.↗

NASA NTRS2017

Beyond Nanopore Sequencing in Space: Identifying the Unknown

Astronaut Kate Rubins sequenced DNA on the International Space Station (ISS) for the first time in August 2016 (Figure 1A). A 2D sequencing library containing an equal mixture of lambda bacteriophage, Escherichia coli, and Mus musculus was prepared on the ground with a SQK_MAP006 kit and sent to the ISS frozen and loaded into R7.3 flow cells. After a total of 9 on-orbit sequencing runs over 6 months, it was determined that there was no decrease in sequencing performance on-orbit compared to ground controls (1). A total of ~280,000 and ~130,000 reads generated on-orbit and on the ground, respectively, identified 90% of reads that were attributed to 30% lambda bacteriophage, 30% Escherichia coli, and 30% M. musculus (Figure 1B). Extensive bioinformatics analysis determined comparable 2D and 1D read accuracies between flight and ground runs (Figure 1C), and data collected from the ISS were able to construct directed assemblies of E.coli and lambda genomes at 100% and M. musculus mitochondrial genome at 96.7%. These findings validate sequencing as a viable option for potential on-orbit applications such as environmental microbial monitoring and disease diagnosis. Current microbial monitoring of the ISS applies culture-based techniques that provide colony forming unit (CFU) data for air, water, and surface samples. The identity of the cultured microorganisms in unknown until sample return and ground-based analysis, a process that can take up to 60 days. For sequencing to benefit ISS applications, spaceflight-compatible sample preparation techniques are required. Subsequent to the testing of the MinION on-orbit, a sample-to-sequence method was developed using miniPCR™ and basic pipetting, which was only recently proven to be effective in microgravity. The work presented here details the in- flight sample preparation process and the first application of DNA sequencing on the ISS to identify unknown ISS-derived microorganisms.

Stahl, Sarah E.↗

DOE OSTI2022

Multiple Cases of Bacterial Sequence Erroneously Incorporated Into Publicly Available Chloroplast Genomes

Public sequencing databases are invaluable resources to biological researchers, but assessing data veracity as well as the curation and maintenance of such large collections of data can be challenging. Genomes of eukaryotic organelles, such as chloroplasts and other plastids, are particularly susceptible to assembly errors and misrepresentations in these databases due to their close evolutionary relationships with bacteria, which may co-occur within the same environment, as can be the case when sequencing plants. Here, based on sequence similarities with bacterial genomes, we identified several suspicious chloroplast assemblies present in the National Institutes of Health (NIH) Reference Sequence (RefSeq) collection. Investigations into these chloroplast assemblies reveal examples of erroneous integration of bacterial sequences into chloroplast ribosomal RNA (rRNA) loci, often within the rRNA genes, presumably due to the high similarity between plastid and bacterial rRNAs. The bacterial lineages identified within the examined chloroplasts as the most likely source of contamination are either known associates of plants, or co-occur in the same environmental niches as the examined plants. Modifications to the methods used to process untargeted ‘raw’ shotgun sequencing data from whole genome sequencing efforts, such as the identification and removal of bacterial reads prior to plastome assembly, could eliminate similar errors in the future.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Monomer-scale design of functional protein polymers using consensus repeat sequences

Protein-based polymers possess chemically defined sequences that can encode diverse properties and functions into a new class of biopolymeric materials. However, sequence variation that emerges from evolution can obscure the sequence–function relationships of naturally derived polymers. One strategy to clarify these relationships is to identify common sequences between proteins with similar functions. These conserved sequences often emerge from repeat proteins, and “consensus repeat sequences” provide a convenient platform for systematic investigations of biopolymer sequence–property relationships. In this review, we highlight recent approaches to engineer tunable polymeric materials using monomer-scale design of consensus repeat proteins. Here, we explore established and emerging protein-based materials with mechanical resilience, thermodynamic phase behavior, chemical responsiveness, biomolecular transport, and hierarchical structure. Overall, recent advances in the monomer-scale design of repetitive protein polymers present exciting fundamental and translational opportunities for polymer scientists and engineers.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

Understanding how a macromolecule’s primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using matrix-assisted laser desorption/ionization and tandem mass spectrometry (MALDI-MS/MS), and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived “motifs” to inform a machine-learning algorithm toward conformation prediction. Here, this multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

data-driven analysis↗

DOE OSTI2024

Evaluation of the Impact of Concentration and Extraction Methods on the Targeted Sequencing of Human Viruses from Wastewater

Sequencing human viruses in wastewater is challenging due to their low abundance compared to the total microbial background. This study compared the impact of four virus concentration/extraction methods (Innovaprep, Nanotrap, Promega, and Solids extraction) on probe-capture enrichment for human viruses followed by sequencing. Different concentration/extraction methods yielded distinct virus profiles. Innovaprep ultrafiltration (following solids removal) had the highest sequencing sensitivity and richness, resulting in the successful assembly of several near-complete human virus genomes. However, it was less sensitive in detecting SARS-CoV-2 by digital polymerase chain reaction (dPCR) compared to Promega and Nanotrap. Across all preparation methods, astroviruses and polyomaviruses were the most highly abundant human viruses, and SARS-CoV-2 was rare. These findings suggest that sequencing success can be increased using methods that reduce nontarget nucleic acids in the extract, though the absolute concentration of total extracted nucleic acid, as indicated by Qubit, and targeted viruses, as indicated by dPCR, may not be directly related to targeted sequencing performance. Further, using broadly targeted sequencing panels may capture viral diversity but risks losing signals for specific low-abundance viruses. Overall, this study highlights the importance of aligning wet lab and bioinformatic methods with specific goals when employing probe-capture enrichment for human virus sequencing from wastewater.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2004

Development of a State Machine Sequencer for the Keck Interferometer: Evolution, Development and Lessons Learned using a CASE Tool Approach

This paper presents a discussion of the evolution of a sequencer from a simple EPICS (Experimental Physics and Industrial Control System) based sequencer into a complex implementation designed utilizing UML (Unified Modeling Language) methodologies and a CASE (Computer Aided Software Engineering) tool approach. The main purpose of the sequencer (called the IF Sequencer) is to provide overall control of the Keck Interferometer to enable science operations be carried out by a single operator (and/or observer). The interferometer links the two 10m telescopes of the W. M. Keck Observatory at Mauna Kea, Hawaii. The IF Sequencer is a high-level, multi-threaded, Hare1 finite state machine, software program designed to orchestrate several lower-level hardware and software hard real time subsystems that must perform their work in a specific and sequential order. The sequencing need not be done in hard real-time. Each state machine thread commands either a high-speed real-time multiple mode embedded controller via CORB A, or slower controllers via EPICS Channel Access interfaces. The overall operation of the system is simplified by the automation. The UML is discussed and our use of it to implement the sequencer is presented. The decision to use the Rhapsody product as our CASE tool is explained and reflected upon. Most importantly, a section on lessons learned is presented and the difficulty of integrating CASE tool automatically generated C++ code into a large control system consisting of multiple infrastructures is presented.

interferometer↗

NASA NTRS1995

Evaluation of nearest-neighbor methods for detection of chimeric small-subunit rRNA sequences

Detection of chimeric artifacts formed when PCR is used to retrieve naturally occurring small-subunit (SSU) rRNA sequences may rely on demonstrating that different sequence domains have different phylogenetic affiliations. We evaluated the CHECK_CHIMERA method of the Ribosomal Database Project and another method which we developed, both based on determining nearest neighbors of different sequence domains, for their ability to discern artificially generated SSU rRNA chimeras from authentic Ribosomal Database Project sequences. The reliability of both methods decreases when the parental sequences which contribute to chimera formation are more than 82 to 84% similar. Detection is also complicated by the occurrence of authentic SSU rRNA sequences that behave like chimeras. We developed a naive statistical test based on CHECK_CHIMERA output and used it to evaluate previously reported SSU rRNA chimeras. Application of this test also suggests that chimeras might be formed by retrieving SSU rRNAs as cDNA. The amount of uncertainty associated with nearest-neighbor analyses indicates that such tests alone are insufficient and that better methods are needed.

NASA Discipline Exobiology↗

NASA NTRS1993

Sequence and structural implications of a bovine corneal keratan sulfate proteoglycan core protein. Protein 37B represents bovine lumican and proteins 37A and 25 are unique

Amino acid sequence from tryptic peptides of three different bovine corneal keratan sulfate proteoglycan (KSPG) core proteins (designated 37A, 37B, and 25) showed similarities to the sequence of a chicken KSPG core protein lumican. Bovine lumican cDNA was isolated from a bovine corneal expression library by screening with chicken lumican cDNA. The bovine cDNA codes for a 342-amino acid protein, M(r) 38,712, containing amino acid sequences identified in the 37B KSPG core protein. The bovine lumican is 68% identical to chicken lumican, with an 83% identity excluding the N-terminal 40 amino acids. Location of 6 cysteine and 4 consensus N-glycosylation sites in the bovine sequence were identical to those in chicken lumican. Bovine lumican had about 50% identity to bovine fibromodulin and 20% identity to bovine decorin and biglycan. About two-thirds of the lumican protein consists of a series of 10 amino acid leucine-rich repeats that occur in regions of calculated high beta-hydrophobic moment, suggesting that the leucine-rich repeats contribute to beta-sheet formation in these proteins. Sequences obtained from 37A and 25 core proteins were absent in bovine lumican, thus predicting a unique primary structure and separate mRNA for each of the three bovine KSPG core proteins.

NASA Discipline Cell Biology↗

DOE OSTI2025

Structure–Function Relationships in Sequence-Controlled Copolymers for Rare Earth Element Chelation

The ability to tune material function through primary sequence is a defining feature of biological macromolecules, allowing precise control over structure and target interactions in complex aqueous environments. However, translating sequence–structure–function relationships to synthetic macromolecules is challenging due to their dispersity in sequence, conformation, and composition. Here, we report systematic studies of amphiphilic polymer chelators designed to probe how composition and patterning influence binding affinity and selectivity for rare earth elements (REEs), a series of technologically relevant metals with challenging separation profiles. A library of copolymers varying hydrophobic monomer composition and patterning was synthesized via reversible addition–fragmentation chain transfer (RAFT) polymerization, spanning statistical, gradient, and block architectures. REE binding was quantified using a high-throughput colorimetric assay, and reconstruction of polymer ensembles using kinetic stochastic simulations enabled quantitative comparisons of sequence heterogeneity, linking local monomer colocalization to emergent REE binding. Further, we investigated the role of different hydrophobic comonomers in tuning metal coordination, with binding trends linked to structural features that influence binding site desolvation. Complementary dynamic light scattering (DLS) and small-angle X-ray scattering (SAXS) measurements showed that both polymer and monomer architecture modulate metal-induced conformational changes, and that multichain assembly behavior emerges beyond critical hydrophobic thresholds. Sequence control also altered REE selectivity, with nonmonotonic differences observed across compositionally identical polymers with different sequence architectures. Together, these findings establish design principles that connect polymer sequence and structure to binding performance, guiding the design of macromolecular chelators with enhanced affinity and selectivity for applications in separations, sensing, and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Sequence-structure-function characterization of the emerging tetracycline destructase family of antibiotic resistance enzymes

Tetracycline destructases (TDases) are flavin monooxygenases which can confer resistance to all generations of tetracycline antibiotics. The recent increase in the number and diversity of reported TDase sequences enables a deep investigation of the TDase sequence-structure-function landscape. Here, we evaluate the sequence determinants of TDase function through two complementary approaches: (1) constructing profile hidden Markov models to predict new TDases, and (2) using multiple sequence alignments to identify conserved positions important to protein function. Using the HMM-based approach we screened 50 high-scoring candidate sequences in Escherichia coli, leading to the discovery of 13 new TDases. The X-ray crystal structures of two new enzymes from Legionella species were determined, and the ability of anhydrotetracycline to inhibit their tetracycline-inactivating activity was confirmed. Using the MSA-based approach we identified 31 amino acid positions 100% conserved across all known TDase sequences. The roles of these positions were analyzed by alanine-scanning mutagenesis in two TDases, to study the impact on cell and in vitro activity, structure, and stability. These results expand the diversity of TDase sequences and provide valuable insights into the roles of important residues in TDases, and flavin monooxygenases more broadly.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

ULTRA-effective labeling of tandem repeats in genomic sequence

In the age of long read sequencing, genomics researchers now have access to accurate repetitive DNA sequence (including satellites) that, due to the limitations of short read-sequencing, could previously be observed only as unmappable fragments. Tools that annotate repetitive sequence are now more important than ever, so that we can better understand newly uncovered repetitive sequences, and also so that we can mitigate errors in bioinformatic software caused by those repetitive sequences. To that end, we introduce the 1.0 release of our tool for identifying and annotating locally repetitive sequence, ULTRA Locates Tandemly Repetitive Areas (ULTRA). ULTRA is fast enough to use as part of an efficient annotation pipeline, produces state-of-the-art reliable coverage of repetitive regions containing many mutations, and provides interpretable statistics and labels for repetitive regions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗

DOE OSTI2021

Chemical enrichment and radial migration in the Galactic disc – the origin of the [αFe] double sequence

The ([α/Fe], [Fe/H]) distribution of Milky Way stars shows at least two distinct sequences, which have traditionally been associated with the thin and thick disc components. The abundance distribution varies systematically with location R and |z| across the Galaxy. We reproduce this using an analytical chemodynamical model that includes the effects of radial migration and kinematic heating. Unlike some earlier models, our scheme does not require a distinct thick disc component emerging from a separate evolutionary path. The proposed model has a continuous star formation history and a continuous age velocity dispersion relation. Moreover, [α/Fe] is constant for stellar ages less than 8 Gyr, but increases sharply for older stars over a time-scale of 1.5 Gyr. The gap between the two sequences is due to this sharp transition. We show that the high-[α/Fe] sequence at the low-metallicity end is simply a pile-up of old stars, but towards the high-metallicity end, the age progressively decreases and stars have small birth radii. Our model successfully explains the uniformity of the locus of the high-[α/Fe] sequence across different locations. The low-[α/Fe] sequence contains stars with different birth radii that owes its existence to radial migration. For the low-[α/Fe] stars, angular momentum is anticorrelated with [Fe/H], while the opposite is true for high-[α/Fe] stars. We show that the later trend can be explained by the increase of circular velocity with time. If radial migration is not included, the model fails to generate the double sequence and instead shows only a single sequence. Our simple scheme has major advantages over earlier chemodynamical models, as we show.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world’s largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

59 BASIC BIOLOGICAL SCIENCES↗